In this paper, a self-tuning adaptive neural controller strategy for unknown nonlinear system is presented. The system considered is described by an unknown NARMA-L2 model and a feedforward neural network is used to learn the model with two stages. The first stage is learned off-line with two configuration serial-parallel model & parallel model to ensure that model output is equal to actual output of the system & to find the jacobain of the system. Which appears to be of critical importance parameter as it is used for the feedback controller and the second stage is learned on-line to modify the weights of the model in order to control the variable parameters that will occur to the system. A back propagation neural network is appl

Abstract

 Metal cutting processes still represent the largest class of manufacturing operations. Turning is the most commonly employed material removal process. This research focuses on analysis of the thermal field of the oblique machining process. Finite element method (FEM) software DEFORM 3D V10.2 was used together with experimental work carried out using infrared image equipment, which include both hardware and software simulations. The thermal experiments are conducted with AA6063-T6, using different tool obliquity, cutting speeds and feed rates. The results show that the temperature relatively decreased when tool obliquity increases at different cutting speeds and feed rates, also it

This paper develops a fuzzy multi-objective model for solving aggregate production planning problems that contain multiple products and multiple periods in uncertain environments. We seek to minimize total production cost and total labor cost. We adopted a new method that utilizes a Zimmermans approach to determine the tolerance and aspiration levels. The actual performance of an industrial company was used to prove the feasibility of the proposed model. The proposed model shows that the method is useful, generalizable, and can be applied to APP problems with other parameters.

Periodontal diseases are inflammatory diseases, for which, scaling and root planning is the main approach. Diode laser therapy as an adjunct to non-surgical periodontal treatment has shown some beneficial effects.

Aim: The objective of this single randomized controlled clinical study was to assess the effect of a 940 nm diode laser as an adjunct to SRP therapy in the treatment of periodontal pockets.

 Methods: In this study, twenty patients in need of periodontal treatment with periodontal pocket ≥ 4 mm were selected for this split-mouth clinical study. Test group treated by diode laser 940 nm as an adjunct with SRP, control group treated by SRP in contralateral quadrants. Clinical

NAA Mustafa, Journal of the Sixth Conference of the Faculty of Languages, 2010

The results of theoretical and experimental investigations carried out to study the effect of load and relative sliding speed on the abrasive wear behavior in drilling bit teeth surfaces of an insert tungsten carbide bit have been presented. Experimentally, an apparatus for abrasive wear tests conducted on the modified ASTM-G65 was modified and fabricated to facilitate loading and measurement of wear rate for the sand/ steel wheel abrasion test, which involves two cases of contact; first is at dry sand and second is under wet condition. These tests have been carried under varied operating parameters of normal load and sliding speed. A theoretical model based upon the Archard equation has been developed for predicting wear simulation by u

Fuzzy logic is used to solve the load flow and contingency analysis problems, so decreasing computing time and its the best selection instead of the traditional methods. The proposed  method is very accurate with outstanding computation time, which made the fuzzy load flow (FLF) suitable for real time application for small- as well as large-scale power systems. In addition that, the FLF efficiently able to solve load flow problem of ill-conditioned power systems and contingency analysis. The FLF method using Gaussian membership function requires less number of iterations and less computing time than that required in the FLF method using triangular membership function. Using sparsity technique for the input Ybus sparse matrix data gi

The international reporting auditor witness rapidly developed over the past years, where profession began give attention to the development of auditor reporting and improve its informational report through the issuance and amendment of some relevant international auditing standards. The reality of the situation refers to the failure to inform the auditor in Iraq in  many areas, including: Clearly defined management responsibility for the preparation of financial and auditor's responsibility to express an opinion on these statements and Amendment of opinion when the financial statements as a whole is free from material misstatement based on the evidence is sufficient and appropriate audit, or not to build the auditor's ability to obt

           This paper introduce two types of edge degrees (line degree and near line degree) and total edge degrees (total line degree and total near line degree) of an edge in a fuzzy semigraph, where a fuzzy semigraph is defined as (V, σ, μ, η) defined on a semigraph G^* in which σ : V → [0, 1], μ : VxV → [0, 1] and η : X → [0, 1] satisfy the conditions that for all the vertices u, v in the vertex set,  μ(u, v) ≤ σ(u) ᴧ σ(v) and  η(e) = μ(u₁, u₂) ᴧ μ(u₂, u₃) ᴧ … ᴧ μ(u_n-1, u_n) ≤ σ(u₁) ᴧ σ(u_n), if e = (u₁, u₂, …, u_n), n ≥ 2 is an edge in the semigraph G

     Recently Tobit  Quantile Regression(TQR) has emerged as an important tool in statistical analysis . in order to improve the parameter estimation in (TQR) we proposed Bayesian hierarchical model with double adaptive elastic net technique  and Bayesian hierarchical model with adaptive ridge regression technique .

 in double adaptive elastic net technique we assume  different penalization parameters  for penalization different regression coefficients in both parameters λ₁and  λ₂  , also in adaptive ridge regression technique we assume different  penalization parameters for penalization different regression coefficients i